Dave Burstein

Rapid coverage of AI. Many tweets. @AIPrimes has just the most interesting. DM open.

[Dave Burstein @AInews_wire]

"Frontier intelligence belongs to everyone" @Yulan_du of Kimi. Xi and 90% of the world agree while the US giants demand rule. Biggest AI policy issue ever. I'll report soon.

[Dave Burstein @AInews_wire]

https://t.co/quteD4wYPs

[Dave Burstein @AInews_wire]

Japan Inc is spending probably $20B on a multimodel domestic LLM Noetra. Physical AI for robots & cars. Honda's investing. Part of the worldwide move to break free of America's yoke. #digitalsovereignty

[Dave Burstein @AInews_wire]

https://t.co/BsUs3x8R15

[Dave Burstein @AInews_wire]

In 2024, I wrote "Bigger is not (that much) better" as progress on Llama slowed. @DarioAmodei remained a true believer. In 2026, progress sped up dramatically as AIs write code. @alexreisner needs to look again. But he's right AI doesn't scale well with users, a big cost problem

[张小珺 Xiaojun Zhang @zhang_benita]

This was my first interview with Yang Zhilin, founder of Kimi, conducted in early 2024 and published on March 1, 2024—exactly the first anniversary of Kimi's founding. At the time, Kimi had only 80 people, working out of their first, somewhat run-down office. There was no logo at the entrance. Only a white piano standing guard by the door.

This article generated quite a stir in China's tech community at the time. The original title of this piece is quite poetic: March Toward the Endless, Unknown Snow Mountains.

Back then, I was still a print journalist, so this interview exists only as text and an audio podcast.

As we can see, many of the views expressed in this article have since been borne out.

Just rereading these words from two years ago, you really can't help but marvel at how dramatically the world has changed!

[Dave Burstein @AInews_wire]

https://t.co/uXt2XVZg5C

[Dave Burstein @AInews_wire]

Chain of thought - the heart of many reasoning models - was apparently developed at 4Chan by gamers a year before Google believed it invented it

[Michael Guo @Michaelzsguo]

Why did Kimi CEO Yang Zhilin return to China rather than stay in the U.S.?

In some of his early interviews, he explained his thinking. His answer was more practical than ideological.

In his view, China had become a sufficiently complete environment for pursuing frontier AI: policy support, venture capital, accumulated talent, a strong domestic industry, and a large user base.

He summarized one reason in two words:
“环境完备。”
“The environment was complete.”

Yang was not claiming that the U.S. lacked talent or capital. He had studied at Carnegie Mellon and worked at Facebook AI Research and Google Brain. He understood the American ecosystem firsthand.

His question was: where could he assemble enough researchers, capital, computing, engineering, product capability, and users to build an AGI company from scratch?

In another interview, he put the resource problem bluntly:
“它需要人才聚集、资本聚集。”
“It requires a concentration of talent and capital.”

This was not a small research project. While still in the U.S., Yang calculated that a serious AGI startup would need at least $100 million almost immediately.

The second reason was timing.
Yang believed that by late 2022, several conditions had converged:
the internet had accumulated enormous amounts of data;
Transformer architectures had become scalable;
semiconductor progress made large-scale training possible;
scaling laws suggested that more computation could produce more intelligence;
ChatGPT showed that AI could reach ordinary users.
The opportunity was no longer merely to publish papers. It was to build a company combining research, engineering, product, and commercialization.

Yang described that organization as:
“科学、工程和商业的结合。”
“A combination of science, engineering, and business.”

That explains why Kimi began as a consumer product rather than a pure research lab. Yang wanted to put advanced models in users’ hands, observe how they interacted with them, and use that feedback to shape the technology.

He said:
“AGI最终会是一个跟所有用户co-work产生的东西。”
AGI would ultimately emerge through collaboration with users.

China offered a large, concentrated market for that feedback loop—especially around long context, personalization, complex workflows, and agents.

But Yang’s ambition was not merely domestic. He explicitly said:
“真正AGI肯定是全球化的。”
“True AGI will necessarily be global.”

So the distinction is important:

China was his launch base, not necessarily AGI’s final market.
His metaphor was that internet companies could “plant a tree”—define a product and execute toward it. Large-model companies had to “承包一片森林”—take responsibility for an entire forest whose future growth was unpredictable.

That required enormous resources, but also an organization willing to tolerate uncertainty.

Yang described the founder’s job as:
“爬楼梯，而不只是看风景。”
“Climb the stairs, rather than merely admire the scenery.”

In other words, prioritize improving model capability and exploring the limits of intelligence, while still building a business.

So why did he return?

Because he believed China had become sufficiently complete to support an ambitious AGI startup.
The U.S. gave him world-class training and research experience. China gave him the opportunity to combine capital, talent, engineering, users, and a company into one system.

His decision was therefore less “China versus America” than a strategic judgment:

Build where the necessary conditions are available.
Pursue technology whose ultimate market is global.
And let real users—not just benchmarks—help determine what AGI becomes.

[Michael Guo @Michaelzsguo]

Speaking of Tsinghua, we can’t skip the Yao Class (姚班). As some would say, it has produced the talent behind half of the global AI ecosystem.

https://t.co/PzAiFIkN0m

[Michael Guo @Michaelzsguo]

https://t.co/9ksctlktyu

[Michael Guo @Michaelzsguo]

Moonshot AI, the company behind Kimi, has four core founders. Their backgrounds are unusually strong:

- Founder and CEO Yang Zhilin studied computer science at Tsinghua before earning his PhD from Carnegie Mellon. He was the first author of Transformer-XL and XLNet, and previously worked at FAIR and Google Brain.

- Co-founder and CTO Zhang Yutao earned his PhD in computer science from Tsinghua. His earlier work covered knowledge graphs and AMiner, and he previously co-founded Recurrent AI with Yang.

- Co-founder Wu Yuxin studied at Tsinghua and CMU before joining FAIR. He worked with Kaiming He on Group Normalization and also created Detectron2.

- Co-founder Zhou Xinyu studied computer science at Tsinghua and later joined Megvii, where he worked on turning research algorithms into production systems and co-authored ShuffleNet.

They all share one root: Tsinghua University.

Tsinghua is widely regarded as one of China’s top universities. In the latest U.S. News Best Global Universities ranking, it reached No. 6 worldwide.

Its influence on China’s AI industry extends well beyond Moonshot. https://t.co/DRO96gylNN, the company behind the GLM models, also grew out of Tsinghua. Its co-founder and chief scientist, Tang Jie, was once Yang Zhilin’s teacher.

There is also a more personal connection.

Yang and Zhou formed a rock band together at Tsinghua. Moonshot AI’s Chinese name, 月之暗面, comes from Pink Floyd’s album The Dark Side of the Moon, one of Yang’s favorites.

Kimi may look like a young AI company. Behind it is a much older network of classmates, teachers, research labs, and friendships.

[Yuandong Tian @tydsh]

Chinese students are often down-to-earth do-ers, a critical characteristic in LLM era.

Yuxin Wu was my intern back in 2015 and I spent an hour debating with my former manager on the roof of Facebook building, arguing that he should be hired.

I won the debate by staking my reputation on it. Fortunately I was right.

It used to be the case that the business model is fixed and business workflow clearly decouples into vision + execution. Professional CEO/VP/Director focus on presenting the long-term vision, and junior people sit in the war room to do the grudging work to push the numbers up, and no one knows their names.

Things have changed substantially. The business pattern now depends on the technical strength of the models, which cannot be measured by a pre-defined set of benchmark numbers. Too many ways and too much incentive towards reward hacking, if sitting in a big hierarchy.

Technical-first now becomes critical. Sit down and get things to work. Get hands dirty, check the data and code, fast feedback loop, step out of the echo chamber, tear the pretty story apart and rewrite, ready to say "I am wrong". Let experiments tell the issues and be humble in front of AI.

That's why down-to-earth doers shine now. This applies to everyone including co-founders. Anything else follows.

[Yu Xiang @YuXiang_IRVL]

This isn’t surprising to me. Physical Intelligence has some of the best robot learning researchers out there.

[CG @cgtwts]

Moonshot AI CEO Yang Zhilin just gave one of the clearest masterclasses on how frontier AI models are actually built.

[Evan Kirstel #B2B #TechFluencer @EvanKirstel]

@Kimi_Moonshot

[AdiiX @adiix_official]

THIS DEVELOPER JUST KILLED THE ENTIRE VOICE CLONING INDUSTRY WITH ONE GITHUB REPO

Claude now speaks in your own voice across 23 languages through a single MCP call.

Free. Local. Offline.

ElevenLabs charged $22-$330 a month for what Jamie Pine just gave away under an MIT license.

Claude Code, Cursor, and Cline hook in with one command and start replying in your cloned voice straight from the terminal.

→ developer Jamie Pine dropped the repo jamiepine/voicebox on GitHub 41.6k stars in a matter of weeks

→ clones any voice from 10 seconds of audio, seven TTS engines to choose from

→ runs on your own machine via Tauri (Rust, not Electron) voice and samples never leave your computer

→ Claude Code, Cursor, Cline, and any MCP-aware agent speak back in your chosen clone through a single voicebox.speak call

→ plus global dictation with one hotkey inside any app

→ generate content in Arabic, Japanese, or Polish without opening your mouth

Replaces ElevenLabs and WisprFlow in one MIT-licensed app.

Bookmark this for the moment you want to give your agent a voice, repo below 👇🏻

[Dave Burstein @AInews_wire]

@matthew_d_white What most of the AI world looks like today. A similar group in the US or Europe would have many asians but not as many. How we bring more Latinios, Africans, and women to the fore is one of the key challenges. Everyone would benefit.

[Matt White @matthew_d_white]

Yesterday in Shanghai, after day one of #WAIC2026, I hosted a dinner for AI researchers, engineers, and open source builders working across model training, data engineering, inference, and safety.

The goal was simple: bring the right people into one room.

[Dave Burstein @AInews_wire]

Many of the most respected people in AI have been congratulating @kimi for a remarkable model. Several, like @ZeyuanAllenZhu , are Chinese who have moved to the West, where they found greater opportunity. Will they join the returnees now that Chinese opportunities are clear? The US attacks on China are decimating American AI research. One implication: While DC thinks the US government is supporting AI progress, the net effect of recent US actions has been strongly negative for the US AI future. Chinese, Indian, and other non-US-born researchers have played a crucial role in US progress. Losing them will be devastating.
Western cultures make it difficult for many nurtured in Latin America and Africa to join us. Africans are 18% of the world's people but less than 1% in AI. I am not suggesting quotas or advancing anyone beyond their abilities. I do believe in reaching out, communicating, and breaking down barriers. Everyone will benefit.

[Vincent Chow @vince_chow1]

And the arrival of Fengming himself on X has also single handedly raised the quality of discourse here

Had the pleasure of joining a roundtable with him at @anu_china earlier this year, just a fount of knowledge on Chinese EVs, batteries and AI